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Data Scientist Hiring Hackathon

About the Event

About the Data Scientist Hiring Hackathon

 

Join the Data Scientist Hiring Hackathon, a focused hiring challenge designed to identify strong data science talent for a full-time Data Scientist role. This hackathon evaluates job-ready data science skills through structured, time-bound assessments and a real-world data science problem. 

Participants will be assessed on key areas including Python, Pandas, Data Preprocessing, Exploratory Data Analysis, Statistics, GenAI, and the Classical Machine Learning Lifecycle. 

Whether you are a student, an early-career professional, or a working practitioner, this hiring hackathon provides an opportunity to demonstrate your data science skills and get shortlisted for interviews. 

Top-performing participants will be shortlisted for interview opportunities with the hiring team. 

 

About Analytics Vidhya

 

Analytics Vidhya is India’s largest and one of the world’s leading communities for data science and AI professionals. With over 1.5 million monthly visits and a global community of 5.4 million learners and practitioners, the platform aims to empower students, professionals, and enthusiasts through high-quality content, industry-relevant training, and hiring-focused initiatives. 

The platform brings together the data science ecosystem through in-depth articles, active forums, webinars, certification courses, and hands-on hackathons. By combining learning with real-world hiring opportunities, Analytics Vidhya helps professionals build job-ready skills, stay updated with industry trends, and transition into impactful data and AI roles. 

 

We're Hiring For

 

Role: Data Scientist 
Location: Gurugram (On-site) 

 

What We're Looking For

 

  • Strong foundation in Python and Pandas 
  • Understanding of data preprocessing, exploratory data analysis, statistics, and GenAI 
  • Familiarity with the machine learning lifecycle 
  • Ability to solve analytical and data-driven problems 

 

Test Format and Timeline

 

Round 1: Skill Test (MCQ)

25 multiple-choice questions designed to test fundamental data science knowledge. 

  • Start Date: 16 March 2026 
  • End Date: 1 April 2026 (Midnight) 

 

Round 2: Data Science Problem Statement

Participants will work on a practical data science problem to demonstrate their analytical and modeling skills. 

  • Start Date: 23 March 2026 
  • End Date: 1 April 2026 (Midnight) 

 

Why Participate in This Hiring Hackathon?

 

  • Get assessed using practical, job-relevant data science questions 
  • Showcase your skills directly to the hiring team 
  • Earn an opportunity to interview for a Data Scientist role 
  • Test your knowledge across core data science concepts 
  • Benchmark your performance against other participants 

 

Who Should Participate?

 

  • Aspiring data scientists looking for interview opportunities 
  • Students preparing for data science roles 
  • Working professionals aiming to transition or grow in data science 
  • Professionals working with Python, Pandas, and machine learning workflows 
  • Anyone preparing for data science interviews 
  • Students, professionals, and data enthusiasts passionate about data, analytics, and problem solving 

 

Want to Prepare or Learn More?

 

If you want to strengthen your fundamentals or revise key concepts before participating, explore the Machine Learning Certification Course for Beginners. The course covers Python, Pandas, statistics, and machine learning fundamentals with hands-on exercises and real-world examples. 

Explore the course: 
https://www.analyticsvidhya.com/courses/Machine-Learning-Certification-Course-for-Beginners/?utm_source=datahack&utm_medium=data-scientist-hiring-hackathon 

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Spaces You Can Join

Data Science

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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Generative AI

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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10.4K

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Data Engineering

Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!

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10.4K

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Frequently Asked Questions

Find the answers for the most frequently asked questions

There are no specific requirements to register for the hackathon, although it is recommended to have some basic knowledge of the relevant topics, such as Data Science, Machine Learning, or Deep Learning, along with proficiency in a coding language, preferably Python.

Depending on the type of competition, you can participate individually or in a team.

You can access the problem statement under the "Problem Statement" tab once the Hackathon is live.

Participants benefit from one-on-one feedback, publication on a respected platform, recognition from a global audience, and monetary rewards for each published article. Additionally, the top articles receive special rewards.

Each article must be original, and pass plagiarism and not AI generated content checks. You can submit multiple articles as long as each is distinct. Proper citation of all references and image sources is mandatory.

In the Blogathon, an article typically explores a specific topic or idea within Data Science or Generative AI and is required to be at least 1000 words long. A guide, on the other hand, is a more comprehensive resource, covering all aspects of a particular subject in data science, and must be at least 2500 words long. Guides aim to serve as a one-stop resource, providing detailed insights and practical applications, whereas articles might focus on narrower or more specific topics.

Multiple submissions of the same article are prohibited and could lead to disqualification. Articles failing to meet the required length, originality, or citation standards will be rejected.

AVCC is a community for authors who have had three or more articles published in the Blogathons. Members benefit from monetary rewards for each published article and get the opportunity to showcase their work to a larger audience.